People are just naturally much better at "guessing" randomly than computers are.... I guess?

I'd guess the trick is the computer can only do what its told, so its partly on that and any blind-spots the programmers had. It can't improvise, guess, or go "eureka!", nor think outside its programmed box.

edit: in short, when the new ideas were added in, the computer did better because of it. Everybody is learning and improving along with the program!

I'd argue the exact opposite, ToolGuy3. The human gamers learned the basic rules, and are clearly using their intelligence to set ground rules, and designing molecules that work much better than a mechanical process.

The computer just follows the "laws of nature" as given to it by the programmers. The humans have the same laws, but can apply intelligence.

The real question here is this: given both the computer and the gamers molecules--is there any evidence just from examining the molecules that one is designed, and the other is generated by the computer?

I'd argue the exact opposite, ToolGuy3. The human gamers learned the basic rules, and are clearly using their intelligence to set ground rules, and designing molecules that work much better than a mechanical process.

The computer just follows the "laws of nature" as given to it by the programmers. The humans have the same laws, but can apply intelligence.

The real question here is this: given both the computer and the gamers molecules--is there any evidence just from examining the molecules that one is designed, and the other is generated by the computer?

Well, it was just a joke, but even so, greater variety than pre-programmed algorithms is still more or less random chance and the intermediate goal was "energetically stable", which is exactly what you would expect with random evolution. The end result ("animal" or whatever) doesn't seem to be known at all.

Edit: Clearly, I'm not as funny as I thought I was. My only real point was that you need lots more "random" (either actually or apparently) choices to have the best chance of finding energetically stable combinations. A few billion years would probably work and we could probably do it faster.

I agree that the interesting question is if the molecules look designed or not. I'm guessing that these will be considerably more "logical" than our own rather haphazard genome.

So if I'm understanding this correctly, a bunch of amateurs basically guessing i.e. random chance, works better than the experts i.e. Intelligent Design.

Hmmm......

I don't think that's it. I mean, the gamers weren't doing stuff by random, as they were introduced to the laws that govern RNA in the form of tutorials, so they didn't start from scratch, and repeatedly iterated on their own designs in order to perform better. The article stated that, after six iterations, the gamers' algorithms were better than the state-of-the-art system's, which would mean there's nothing random, instead the know-how was improved over each time.This is more like what Genetic Algorithms would behave, but instead of entering randomized individuals, the individuals at the initial generation were based on the gamer's grasp of the rules, intuition and a little bit of luck.And hey, the lab-coat guys might be experts, but everyone can learn to do better!

It's reassuring that there are still some games where humans do better than computers. I guess I shouldn't underestimate the power of communal knowledge in solving problems [games], enabled by online communication.

Keep in mind that this is still community-generated, from what I can tell. It's not like individual people were coming up with the best structures, right?

Though it strikes me as odd that no one previously thought of putting a G-C pair at the base of a stem. Really? I'm getting my Ph.D. in biochemistry and it seems like that's a basic thing that anyone working with DNA or RNA should have thought of.

EDIT: For those who don't know, G-C pairs are stronger because there are 3 bonds between them rather than the 2 for A-T, so G-C pairs are often used as "clamps" when designing an oligonucleotide primer for polymerase chain reactions that amplify a DNA sequence, which is more efficient when the polymerase enzyme can bind to a strongly-bound end.

Empirical science at its best. Pattern matching and thinking outside the box is what humans excel at, so it's not surprising that they were able to beat the existing algo's. Still, good to see science input from the masses.

People are just naturally much better at "guessing" randomly than computers are.... I guess?

Alas(?) no, computers produce better "random" numbers than people by many orders of magnitude. What people do is analysis, on both a conscious and sub-conscious level. We're ridiculously good at noticing patterns and do well extrapolating from them. So you throw thousands of people at a problem like this and what you'd expect to see is what actually happened: At first people were largely guessing and didn't know all the rules, so they did poorly. The longer they had to work the more they noticed patterns that worked and the more custom rules they built, leading to steadily improving results.

So if I'm understanding this correctly, a bunch of amateurs basically guessing i.e. random chance, works better than the experts i.e. Intelligent Design.

Hmmm......

See above: This wasn't random. If it was guessing at random then there'd be no real "state of the art" algorithm, you'd just perform a bunch of random changes to some RNA, synth it, and test it to see.

Though it strikes me as odd that no one previously thought of putting a G-C pair at the base of a stem. Really? I'm getting my Ph.D. in biochemistry and it seems like that's a basic thing that anyone working with DNA or RNA should have thought of.

No, the gamers came up with a mix of known and unknown rules. That was one of the known ones; i used it as an example because it was illustrative for people who don't know biochemistry, and easy to interpret for those who do.

An example of the unknown stuff would be what to put in the loop next to the G-C pairs in the stem.

Though it strikes me as odd that no one previously thought of putting a G-C pair at the base of a stem. Really? I'm getting my Ph.D. in biochemistry and it seems like that's a basic thing that anyone working with DNA or RNA should have thought of.

No, the gamers came up with a mix of known and unknown rules. That was one of the known ones; i used it as an example because it was illustrative for people who don't know biochemistry, and easy to interpret for those who do.

An example of the unknown stuff would be what to put in the loop next to the G-C pairs in the stem.

People are just naturally much better at "guessing" randomly than computers are.... I guess?

Alas(?) no, computers produce better "random" numbers than people by many orders of magnitude. What people do is analysis, on both a conscious and sub-conscious level. We're ridiculously good at noticing patterns and do well extrapolating from them. So you throw thousands of people at a problem like this and what you'd expect to see is what actually happened: At first people were largely guessing and didn't know all the rules, so they did poorly. The longer they had to work the more they noticed patterns that worked and the more custom rules they built, leading to steadily improving results.

So if I'm understanding this correctly, a bunch of amateurs basically guessing i.e. random chance, works better than the experts i.e. Intelligent Design.

Hmmm......

See above: This wasn't random. If it was guessing at random then there'd be no real "state of the art" algorithm, you'd just perform a bunch of random changes to some RNA, synth it, and test it to see.

Of course, one of our best ways to construct AI is to use evolutionary algorithms. The design is the intelligence.

What exactly is happening inside the heads of those humans, to beat the computers? Some sort of very plastic pattern recognition is feeding the trial and error, and that seems crucial. After all, the bit we are consciously aware of feels like trial and error where computers are much faster than us. Somehow we overlay with patterns which are chosen below conscious guidance and those prune our choices.

Not impressed with the design in the article. That sucker's going to be way too wobbly and definitely needs more struts.

On a serious note, this is very cool but maybe not too surprising that the gamers can beat the algorithms. This is basically a puzzle in optimising conditions according to an arbitrary set of rules to obtain the desired outcome - aka min-maxing. And if there's one thing that gamers excel at its min-maxing. See any games forum at all where the game involves a modest number of variables - it doesn't take long at all to see the 'best' builds popping up.

The AI in any game always pales in comparison to a good player. Usually the AI can only win by cheating. One of the other things humans have over an algorithm is that they can predict what will happen in certain scenarios and this becomes a part of their design process. Sort of like bite sized rapid prototyping that is internalized to the person's brain. The more experience a person gets, the more accurate and fast a person's prediction becomes. This is more or less a big part of how anyone gets better at any activity.

An algorithm on the other has a fixed set of rules it operates on. A programmer can possibly build in limited predictive cases, but they are restricted by what the programmer knows and can implement. Additionally an algorithm is pure trial and error. It cannot learn from its failures and it cannot rewrite its own rules.

Stuff like this sometimes makes me wonder if I'm wasting my comp's time on BOINC projects. They farm off work for the comp to crunch on using algorithms. But, if the algorithms aren't very good, then it's just a waste of time.

If we can make more games out of science research, I'm sure there'd be tons of asians folks that would show just how amazing they are at beating the pants off of gamification.

The AI in any game always pales in comparison to a good player. Usually the AI can only win by cheating. One of the other things humans have over an algorithm is that they can predict what will happen in certain scenarios and this becomes a part of their design process. Sort of like bite sized rapid prototyping that is internalized to the person's brain. The more experience a person gets, the more accurate and fast a person's prediction becomes. This is more or less a big part of how anyone gets better at any activity.

An algorithm on the other has a fixed set of rules it operates on. A programmer can possibly build in limited predictive cases, but they are restricted by what the programmer knows and can implement. Additionally an algorithm is pure trial and error. It cannot learn from its failures and it cannot rewrite its own rules.

I'd argue the exact opposite, ToolGuy3. The human gamers learned the basic rules, and are clearly using their intelligence to set ground rules, and designing molecules that work much better than a mechanical process.

The computer just follows the "laws of nature" as given to it by the programmers. The humans have the same laws, but can apply intelligence.

The real question here is this: given both the computer and the gamers molecules--is there any evidence just from examining the molecules that one is designed, and the other is generated by the computer?

Well, it was just a joke, but even so, greater variety than pre-programmed algorithms is still more or less random chance and the intermediate goal was "energetically stable", which is exactly what you would expect with random evolution. The end result ("animal" or whatever) doesn't seem to be known at all.

I think you may be confusing evolution and mutation. Evolution is not random. Mutation is random, and most of the time a random mutation is useless or even damaging. The small subset of the random mutations that are actually useful are weeded out by the selection part, that is usually not random at all.

Mutations that are beneficial give the organism a better chance to survive and reproduce, so they are kept. Mutations that are lowering the survival chance the organism or making reproduction hard do not survive, and are lost. So selection is not random, making evolution also not random.

It's reassuring that there are still some games where humans do better than computers. I guess I shouldn't underestimate the power of communal knowledge in solving problems [games], enabled by online communication.

It's no different than cellular automama.

Humans have built turing complete computers out of game of life, but a computer can't tell you what the next state is without advancing the state.